Displaying publications 1 - 20 of 80 in total

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  1. Pitisuttithum P, Chan WK, Goh GB, Fan JG, Song MJ, Charatcharoenwitthaya P, et al.
    World J Gastroenterol, 2020 May 21;26(19):2416-2426.
    PMID: 32476802 DOI: 10.3748/wjg.v26.i19.2416
    BACKGROUND: Gamma-glutamyl transferase (GGT) is associated with the risk of cardiovascular disease (CVD) in the general population.

    AIM: To identify the association of baseline GGT level and QRISK2 score among patients with biopsy-proven nonalcoholic fatty liver disease (NAFLD).

    METHODS: This was a retrospective study involving 1535 biopsy-proven NAFLD patients from 10 Asian centers in 8 countries using data collected by the Gut and Obesity in Asia (referred to as "GO ASIA") workgroup. All patients with available baseline GGT levels and all 16 variables for the QRISK2 calculation (QRISK2-2017; developed by researchers at the United Kingdom National Health Service; https://qrisk.org/2017/; 10-year cardiovascular risk estimation) were included and compared to healthy controls with the same age, sex, and ethnicity. Relative risk was reported. QRISK2 score > 10% was defined as the high-CVD-risk group. Fibrosis stages 3 and 4 (F3 and F4) were considered advanced fibrosis.

    RESULTS: A total of 1122 patients (73%) had complete data and were included in the final analysis; 314 (28%) had advanced fibrosis. The median age (interquartile range [IQR]) of the study population was 53 (44-60) years, 532 (47.4%) were females, and 492 (43.9%) were of Chinese ethnicity. The median 10-year CVD risk (IQR) was 5.9% (2.6-10.9), and the median relative risk of CVD over 10 years (IQR) was 1.65 (1.13-2.2) compared to healthy individuals with the same age, sex, and ethnicity. The high-CVD-risk group was significantly older than the low-risk group (median [IQR]: 63 [59-67] vs 49 [41-55] years; P < 0.001). Higher fibrosis stages in biopsy-proven NAFLD patients brought a significantly higher CVD risk (P < 0.001). Median GGT level was not different between the two groups (GGT [U/L]: Median [IQR], high risk 60 [37-113] vs low risk 66 [38-103], P = 0.56). There was no correlation between baseline GGT level and 10-year CVD risk based on the QRISK2 score (r = 0.02).

    CONCLUSION: The CVD risk of NAFLD patients is higher than that of healthy individuals. Baseline GGT level cannot predict CVD risk in NAFLD patients. However, advanced fibrosis is a predictor of a high CVD risk.

    Matched MeSH terms: Risk Assessment/methods
  2. Luo XS, Imai N, Dorigatti I
    Travel Med Infect Dis, 2020 01 26;33:101562.
    PMID: 31996323 DOI: 10.1016/j.tmaid.2020.101562
    BACKGROUND: No large-scale Zika epidemic has been observed to date in Southeast Asia following the 2015-16 Latin American and the Caribbean epidemic. One hypothesis is Southeast Asian populations' partial immunity to Zika.

    METHOD: We estimated the two conditions for a Zika outbreak emergence in Southeast Asia: (i) the risk of Zika introduction from Latin America and the Caribbean and, (ii) the risk of autochthonous transmission under varying assumptions on population immunity. We also validated the model used to estimate the risk of introduction by comparing the estimated number of Zika seeds introduced into the United States with case counts reported by the Centers for Disease Control and Prevention (CDC).

    RESULTS: There was good agreement between our estimates and case counts reported by the CDC. We thus applied the model to Southeast Asia and estimated that, on average, 1-10 seeds were introduced into Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam. We also found increasing population immunity levels from 0 to 90% reduced probability of autochthonous transmission by 40% and increasing individual variation in transmission further reduced the outbreak probability.

    CONCLUSIONS: Population immunity, combined with heterogeneity in transmission, can explain why no large-scale outbreak was observed in Southeast Asia during the 2015-16 epidemic.

    Matched MeSH terms: Risk Assessment/methods
  3. Borhanuddin B, Mohd Nawi A, Shah SA, Abdullah N, Syed Zakaria SZ, Kamaruddin MA, et al.
    ScientificWorldJournal, 2018;2018:2979206.
    PMID: 30111990 DOI: 10.1155/2018/2979206
    Cardiovascular disease (CVD) leads to high morbidity and mortality rate worldwide. Therefore, it is important to determine the risk of CVD across the sociodemographic factors to strategize preventive measures. The current study consisted of 53,122 adults between the ages of 35 and 65 years from The Malaysian Cohort project during recruitment phase from year 2006 to year 2012. Sociodemographic profile and physical activity level were assessed via self-reported questionnaire, whereas relevant CVD-related biomarkers and biophysical variables were measured to determine the Framingham Risk Score (FRS). The main outcome was the 10-year risk of CVD via FRS calculated based on lipid profile and body mass index (BMI) associated formulae. The BMI-based formula yielded a higher estimation of 10-year CVD risk than the lipid profile-based formula in the study for both males (median = 13.2% and 12.7%, respectively) and females (median = 4.3% and 4.2%, respectively). The subgroup with the highest risk for 10-year CVD events (based on both FRS formulae) was the Malay males who have lower education level and low physical activity level. Future strategies for the reduction of CVD risk should focus on screening via BMI-based FRS in this at-risk subpopulation to increase the cost-effectiveness of the prevention initiatives.
    Study name: The Malaysian Cohort (TMC) project
    Matched MeSH terms: Risk Assessment/methods
  4. Manap N, Voulvoulis N
    Sci Total Environ, 2014 Oct 15;496:607-623.
    PMID: 25108801 DOI: 10.1016/j.scitotenv.2014.07.009
    The aim of this study was to develop a risk-based decision-making framework for the selection of sediment dredging option. Descriptions using case studies of the newly integrated, holistic and staged framework were followed. The first stage utilized the historical dredging monitoring data and the contamination level in media data into Ecological Risk Assessment phases, which have been altered for benefits in cost, time and simplicity. How Multi-Criteria Decision Analysis (MCDA) can be used to analyze and prioritize dredging areas based on environmental, socio-economic and managerial criteria was described for the next stage. The results from MCDA will be integrated into Ecological Risk Assessment to characterize the degree of contamination in the prioritized areas. The last stage was later described using these findings and analyzed using MCDA, in order to identify the best sediment dredging option, accounting for the economic, environmental and technical aspects of dredging, which is beneficial for dredging and sediment management industries.
    Matched MeSH terms: Risk Assessment/methods
  5. Diana Yap FS, Ng ZY, Wong CY, Muhamad Saifuzzaman MK, Yang LB
    Med J Malaysia, 2019 02;74(1):45-50.
    PMID: 30846662
    INTRODUCTION: Increasing incidence of Venous Thromboembolism (VTE) has complicated treatment courses for hospitalised patients. Despite recommendation to support deep vein thrombosis (DVT) risk assessment and appropriate use of prophylaxis in medical inpatients, it is either neglected or prescribed unnecessarily by the clinicians. This study aimed to assess and compare the appropriateness of DVT prophylaxis prescribing between usual care versus a pharmacist-driven DVT Risk Alert Tool (DRAT) intervention among hospitalised medical patients.

    METHODS: A prospective pre- and post-intervention study was conducted among medical inpatients in a Malaysian secondary care hospital. DVT and bleeding risks were stratified using validated Padua Risk Assessment Model (RAM) and International Medical Prevention Registry on Venous Thromboembolism (IMPROVE) Bleeding Risk Assessment Model. Pharmacist-driven DRAT was developed and implemented post-interventional phase. DVT prophylaxis use was determined and its appropriateness was compared between pre and post study using multivariate logistic regression with IBM SPSS software version 21.0.

    RESULTS: Overall, 286 patients (n=142 pre-intervention versus n=144 post-intervention) were conveniently recruited. The prevalence of DVT prophylaxis use was 10.8%. Appropriate thromboprophylaxis prescribing increased from 64.8% to 68.1% post-DRAT implementation. Of note, among high DVT risk patients, DRAT intervention was observed to be a significant predictor of appropriate thromboprophylaxis use (14.3% versus 31.3%; adjusted odds ratio=2.80; 95% CI 1.01 to 7.80; p<0.05).

    CONCLUSION: The appropriateness of DVT prophylaxis use was suboptimal but doubled after implementation of DRAT intervention. Thus, an integrated risk stratification checklist is an effective approach for the improvement of rational DVT prophylaxis use.

    Matched MeSH terms: Risk Assessment/methods*
  6. Jihan AMN, Audey R
    Med J Malaysia, 2023 Mar;78(2):171-176.
    PMID: 36988526
    INTRODUCTION: Risk stratification tools that integrate clinical, ECG findings and cardiac biomarkers have been used to facilitate the management of chest pain patients in the emergency department (ED). We studied the feasibility of history, age, electrocardiogram and risk factors (HEAR) score as a risk stratification tool for chest pain patients presented to ED Hospital Universiti Sains Malaysia (HUSM) in comparison to modified HEART score (MHS) based on major adverse cardiac events (MACE) within 6 weeks' time.

    MATERIALS AND METHODS: We analysed retrospective data of chest pain patients presenting to ED HUSM from 1st June 2020 till 31st January 2021 based on the patient's history, ECG findings, risk factors, age and troponin level. The patients were stratified as low risk (MHS and HEAR score of 0-3), intermediate risk (MHS and HEAR score of 4-6), and high risk (MHS of 7-10 and HEAR score of 7-8). The association of the MHS and HEAR score with MACE at 6 weeks' time was evaluated using simple logistic regression.

    RESULTS: This study included 147 patients in the MHS analysis and 71 patients in HEAR score analysis. The incident rate of MACE in low, intermediate and high risk was 0%,16.3%, and 34.7%, in the MHS group, and 0%, 3.22%, and 6.66% in HEAR score group. The mean difference between MACE and non-MACE in MHS and HEAR score groups was -2.29 (CI: -3.13,1.44, p<0.001) and -2.51(CI: -5.23, 0.21, p=0.070), respectively. There was no significant association between the incidence rate of MACE with modified HEART score (MHS) and HEAR score groups (p>0.95).

    CONCLUSION: HEAR score is not feasible to be used as a risk stratification tool for chest pain patients presenting to ED HUSM in comparison to MHS. Further studies are required to validate the results.

    Matched MeSH terms: Risk Assessment/methods
  7. Salowi MA, Chew FLM, Adnan TH, Ismail M, Goh PP
    Br J Ophthalmol, 2017 Nov;101(11):1466-1470.
    PMID: 28292773 DOI: 10.1136/bjophthalmol-2016-309902
    AIM: To identify the risk indicators for posterior capsular rupture (PCR) in the Malaysian Cataract Surgery Registry (CSR).

    METHODS: Data from the web-based CSR were collected for cataract surgery performed from 2008 to 2013. Data was contributed by 36 Malaysian Ministry of Health public hospitals. Information on patient's age, ethnicity, cause of cataract, ocular and systemic comorbidity, type of cataract surgery performed, local anaesthesia and surgeon's status was noted. Combined procedures and type of hospital admission were recorded. PCR risk indicators were identified using logistic regression analysis to produce adjusted OR for the variables of interest.

    RESULTS: A total of 150 213 cataract operations were registered with an overall PCR rate of 3.2%. Risk indicators for PCR from multiple logistic regression were advancing age, male gender (95% CI 1.04 to 1.17; OR 1.11), pseudoexfoliation (95% CI 1.02 to 1.82; OR 1.36), phacomorphic lens (95% CI 1.25 to 3.06; OR 1.96), diabetes mellitus (95% CI 1.13 to 1.29; OR 1.20) and renal failure (95% CI 1.09 to 1.55; OR 1.30). Surgical PCR risk factors were combined vitreoretinal surgery (95% CI 2.29 to 3.63; OR 2.88) and less experienced cataract surgeons. Extracapsular cataract extraction (95% CI 0.76 to 0.91; OR 0.83) and kinetic anaesthesia were associated with lower PCR rates.

    CONCLUSIONS: This study was agreed with other studies for the risk factors of PCR with the exception of local anaesthesia given and type of cataract surgery. Better identification of high-risk patients for PCR decreases intraoperative complications and improves cataract surgical outcomes.

    Matched MeSH terms: Risk Assessment/methods*
  8. King A, Shipley M, Markus H, ACES Investigators
    Stroke, 2011 Oct;42(10):2819-24.
    PMID: 21852607 DOI: 10.1161/STROKEAHA.111.622514
    Improved methods are required to identify patients with asymptomatic carotid stenosis at high risk for stroke. The Asymptomatic Carotid Emboli Study recently showed embolic signals (ES) detected by transcranial Doppler on 2 recordings that lasted 1-hour independently predict 2-year stroke risk. ES detection is time-consuming, and whether similar predictive information could be obtained from simpler recording protocols is unknown.
    Matched MeSH terms: Risk Assessment/methods
  9. Chia YC
    Singapore Med J, 2011 Feb;52(2):116-23.
    PMID: 21373738
    Cardiovascular Disease (CVD) is the leading cause of death in both developed and developing countries. While it is relatively easy to identify those who are obviously at high risk and those at the lowest risk for CVD, it is often the large group of individuals with what appears to be modestly abnormal risk factors who contributes most to the burden of CVD. This is where estimation of CVD risk is necessary. Many tools for risk assessment have been devised. All these risk scores have their own inherent advantages and disadvantages. Furthermore, they may also not be directly applicable to a local population. Ideally, each country should have its own risk score that takes into account other factors as well. In the interim, it is worthwhile to be familiar with one of these scores, select one that is most appropriate for your patient and discuss treatment options based on the estimated risk.
    Matched MeSH terms: Risk Assessment/methods*
  10. Afifi M
    Singapore Med J, 2006 Jun;47(6):551; author reply 552-3.
    PMID: 16752028
    Comment on: Norsaʼadah B, Rusli BN, Imran AK, Naing L, Winn T. Risk factors of breast cancer in women in Kelantan, Malaysia. Singapore Med J 2005;
    46:698-705
    Matched MeSH terms: Risk Assessment/methods
  11. Saba AO, Ismail A, Zulkifli SZ, Halim MRA, Wahid NAA, Amal MNA
    Sci Rep, 2020 10 14;10(1):17205.
    PMID: 33057156 DOI: 10.1038/s41598-020-74168-9
    The ornamental fish trade has been considered as one of the most important routes of invasive alien fish introduction into native freshwater ecosystems. Therefore, the species composition and invasion risks of fish species from 60 freshwater fish pet stores in Klang Valley, Malaysia were studied. A checklist of taxa belonging to 18 orders, 53 families, and 251 species of alien fishes was documented. Fish Invasiveness Screening Test (FIST) showed that seven (30.43%), eight (34.78%) and eight (34.78%) species were considered to be high, medium and low invasion risks, respectively. After the calibration of the Fish Invasiveness Screening Kit (FISK) v2 using the Receiver Operating Characteristics, a threshold value of 17 for distinguishing between invasive and non-invasive fishes was identified. As a result, nine species (39.13%) were of high invasion risk. In this study, we found that non-native fishes dominated (85.66%) the freshwater ornamental trade in Klang Valley, while FISK is a more robust tool in assessing the risk of invasion, and for the most part, its outcome was commensurate with FIST. This study, for the first time, revealed the number of high-risk ornamental fish species that give an awareness of possible future invasion if unmonitored in Klang Valley, Malaysia.
    Matched MeSH terms: Risk Assessment/methods*
  12. Ho PJ, Lau HSH, Ho WK, Wong FY, Yang Q, Tan KW, et al.
    Sci Rep, 2020 01 16;10(1):503.
    PMID: 31949192 DOI: 10.1038/s41598-019-57341-7
    Incidence of breast cancer is rising rapidly in Asia. Some breast cancer risk factors are modifiable. We examined the impact of known breast cancer risk factors, including body mass index (BMI), reproductive and hormonal risk factors, and breast density on the incidence of breast cancer, in Singapore. The study population was a population-based prospective trial of screening mammography - Singapore Breast Cancer Screening Project. Population attributable risk and absolute risks of breast cancer due to various risk factors were calculated. Among 28,130 women, 474 women (1.7%) developed breast cancer. The population attributable risk was highest for ethnicity (49.4%) and lowest for family history of breast cancer (3.8%). The proportion of breast cancers that is attributable to modifiable risk factor BMI was 16.2%. The proportion of breast cancers that is attributable to reproductive risk factors were low; 9.2% for age at menarche and 4.2% for number of live births. Up to 45.9% of all breast cancers could be avoided if all women had breast density <12% and BMI <25 kg/m2. Notably, sixty percent of women with the lowest risk based on non-modifiable risk factors will never reach the risk level recommended for mammography screening. A combination of easily assessable breast cancer risk factors can help to identify women at high risk of developing breast cancer for targeted screening. A large number of high-risk women could benefit from risk-reduction and risk stratification strategies.
    Matched MeSH terms: Risk Assessment/methods*
  13. Kasim S, Malek S, Cheen S, Safiruz MS, Ahmad WAW, Ibrahim KS, et al.
    Sci Rep, 2022 Oct 20;12(1):17592.
    PMID: 36266376 DOI: 10.1038/s41598-022-18839-9
    Limited research has been conducted in Asian elderly patients (aged 65 years and above) for in-hospital mortality prediction after an ST-segment elevation myocardial infarction (STEMI) using Deep Learning (DL) and Machine Learning (ML). We used DL and ML to predict in-hospital mortality in Asian elderly STEMI patients and compared it to a conventional risk score for myocardial infraction outcomes. Malaysia's National Cardiovascular Disease Registry comprises an ethnically diverse Asian elderly population (3991 patients). 50 variables helped in establishing the in-hospital death prediction model. The TIMI score was used to predict mortality using DL and feature selection methods from ML algorithms. The main performance metric was the area under the receiver operating characteristic curve (AUC). The DL and ML model constructed using ML feature selection outperforms the conventional risk scoring score, TIMI (AUC 0.75). DL built from ML features (AUC ranging from 0.93 to 0.95) outscored DL built from all features (AUC 0.93). The TIMI score underestimates mortality in the elderly. TIMI predicts 18.4% higher mortality than the DL algorithm (44.7%). All ML feature selection algorithms identify age, fasting blood glucose, heart rate, Killip class, oral hypoglycemic agent, systolic blood pressure, and total cholesterol as common predictors of mortality in the elderly. In a multi-ethnic population, DL outperformed the TIMI risk score in classifying elderly STEMI patients. ML improves death prediction by identifying separate characteristics in older Asian populations. Continuous testing and validation will improve future risk classification, management, and results.
    Matched MeSH terms: Risk Assessment/methods
  14. Loh LC, Khoo SK, Quah SY, Visvalingam V, Radhakrishnan A, Vijayasingham P, et al.
    Respirology, 2004 Aug;9(3):379-86.
    PMID: 15363012
    Prediction of mortality in patients with community-acquired pneumonia (CAP) can be assessed using clinical severity scores on admission to hospital. The clinical benefit of such tools is untested in Asian countries. The aim of this study was to determine the early adverse prognostic factors in patients hospitalized with CAP in Malaysia and to assess the usefulness of the British Thoracic Society (BTS) severity criteria.
    Matched MeSH terms: Risk Assessment/methods*
  15. Karunamuni RA, Huynh-Le MP, Fan CC, Thompson W, Eeles RA, Kote-Jarai Z, et al.
    Prostate Cancer Prostatic Dis, 2021 Jun;24(2):532-541.
    PMID: 33420416 DOI: 10.1038/s41391-020-00311-2
    BACKGROUND: Polygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).

    MATERIALS AND METHOD: 180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.

    RESULTS: 166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.

    CONCLUSIONS: Incorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

    Matched MeSH terms: Risk Assessment/methods*
  16. Selvarajah S, Fong AY, Selvaraj G, Haniff J, Uiterwaal CS, Bots ML
    PLoS One, 2012;7(7):e40249.
    PMID: 22815733 DOI: 10.1371/journal.pone.0040249
    Risk stratification in ST-elevation myocardial infarction (STEMI) is important, such that the most resource intensive strategy is used to achieve the greatest clinical benefit. This is essential in developing countries with wide variation in health care facilities, scarce resources and increasing burden of cardiovascular diseases. This study sought to validate the Thrombolysis In Myocardial Infarction (TIMI) risk score for STEMI in a multi-ethnic developing country.
    Matched MeSH terms: Risk Assessment/methods*
  17. Lau KJ, Goh YK, Lai AC
    PLoS One, 2019;14(5):e0216529.
    PMID: 31063498 DOI: 10.1371/journal.pone.0216529
    In this paper, we present a method to estimate the market parameters modelled by an asymmetric jump diffusion process. The method proposed is based on Kou's jump diffusion model while the market parameters refer to the market drift, the market volatility, the jump intensity on market price, and the rate of jump occurrence in a consistent manner throughout the entire paper. The model captures the asymmetric nature of the price fluctuation during up trend markets and down trend markets. The results are compared to conventional options to observe the impact of jump effects. The results from simulation show that the asymmetric jump diffusion model can estimate the fair prices of European call options and annuity better than the Black-Scholes model and the symmetric jump diffusion model proposed by Kou and Merton.
    Matched MeSH terms: Risk Assessment/methods*
  18. Jamal N, Ng KH, Looi LM, McLean D, Zulfiqar A, Tan SP, et al.
    Phys Med Biol, 2006 Nov 21;51(22):5843-57.
    PMID: 17068368
    We describe a semi-automated technique for the quantitative assessment of breast density from digitized mammograms in comparison with patterns suggested by Tabar. It was developed using the MATLAB-based graphical user interface applications. It is based on an interactive thresholding method, after a short automated method that shows the fibroglandular tissue area, breast area and breast density each time new thresholds are placed on the image. The breast density is taken as a percentage of the fibroglandular tissue to the breast tissue areas. It was tested in four different ways, namely by examining: (i) correlation of the quantitative assessment results with subjective classification, (ii) classification performance using the quantitative assessment technique, (iii) interobserver agreement and (iv) intraobserver agreement. The results of the quantitative assessment correlated well (r2 = 0.92) with the subjective Tabar patterns classified by the radiologist (correctly classified 83% of digitized mammograms). The average kappa coefficient for the agreement between the readers was 0.63. This indicated moderate agreement between the three observers in classifying breast density using the quantitative assessment technique. The kappa coefficient of 0.75 for intraobserver agreement reflected good agreement between two sets of readings. The technique may be useful as a supplement to the radiologist's assessment in classifying mammograms into Tabar's pattern associated with breast cancer risk.
    Matched MeSH terms: Risk Assessment/methods*
  19. Tan M, Mariapun S, Yip CH, Ng KH, Teo SH
    Phys Med Biol, 2019 01 31;64(3):035016.
    PMID: 30577031 DOI: 10.1088/1361-6560/aafabd
    Historically, breast cancer risk prediction models are based on mammographic density measures, which are dichotomous in nature and generally categorize each voxel or area of the breast parenchyma as 'dense' or 'not dense'. Using these conventional methods, the structural patterns or textural components of the breast tissue elements are not considered or ignored entirely. This study presents a novel method to predict breast cancer risk that combines new texture and mammographic density based image features. We performed a comprehensive study of the correlation of 944 new and conventional texture and mammographic density features with breast cancer risk on a cohort of Asian women. We studied 250 breast cancer cases and 250 controls matched at full-field digital mammography (FFDM) status for age, BMI and ethnicity. Stepwise regression analysis identified relevant features to be included in a linear discriminant analysis (LDA) classifier model, trained and tested using a leave-one-out based cross-validation method. The area under the receiver operating characteristic (AUC) and adjusted odds ratios (ORs) were used as the two performance assessment indices in our study. For the LDA trained classifier, the adjusted OR was 6.15 (95% confidence interval: 3.55-10.64) and for Volpara volumetric breast density, 1.10 (0.67-1.81). The AUC for the LDA trained classifier was 0.68 (0.64-0.73), compared to 0.52 (0.47-0.57) for Volpara volumetric breast density (p   risk assessment based models. Parenchymal texture analysis has an important role for stratifying breast cancer risk in women, which can be implemented to routine breast cancer screening strategies.
    Matched MeSH terms: Risk Assessment/methods*
  20. Yap PS, Ahmad Kamar A, Chong CW, Yap IK, Thong KL, Choo YM, et al.
    Pathog Glob Health, 2016 Sep;110(6):238-246.
    PMID: 27650884
    The prevalence and antibiotic susceptibility of intestinal carriage of Gram-negative bacteria among preterm infants admitted to the neonatal intensive care unit (NICU) in a tertiary teaching hospital in Malaysia were determined. A total of 34 stool specimens were obtained from preterm infants upon admission and once weekly up to two weeks during hospitalization. The presumptive colonies of Escherichia coli and Klebsiella pneumoniae were selected for identification, antibiotic susceptibility testing, and subtyping by using pulsed-field gel electrophoresis (PFGE). Out of 76 Gram-negative isolates, highest resistance was detected for amoxicillin/clavulanate (30.8%, n = 16), ceftriaxone (42.3%, n = 22), ceftazidime (28.8%, n = 15), cefoxitin (28.8%, n = 15), aztreonam (36.5%, n = 19), and polymyxin B (23.1%, n = 12). Three colistin resistant K. pneumoniae have also been detected based on E-test analysis. Thirty-nine isolates of K. pneumoniae and 20 isolates of E. coli were resistant to more than three antimicrobial classes and were categorized as multidrug resistant (MDR). PFGE analysis revealed a higher diversity in pulsotypes for K. pneumoniae (18 pulsotypes) in comparison to E. coli (four pulsotypes). In addition, a total of fifteen pulsotypes was observed from 39 MDR K. pneumoniae. The risk factors for antibiotic resistance were assessed using random forest analysis. Gender was found to be the most important predictor for colistin resistant while length, OFC, and delivery mode were showing greater predictive power in the polymyxin B resistance. This study revealed worrying prevalence rates of intestinal carriage of multidrug-resistant K. pneumoniae and E. coli of hospitalized preterm infants in Malaysia, particularly high resistance to polymyxins.
    Matched MeSH terms: Risk Assessment/methods
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